The distribution characteristics of blasting pile is an important index indicator to evaluate blasting effect. In view of the inadequacy of the current direct and indirect methods of measuring fragment size of the blast pile, a spatial distribution measurement method for adaptive stratification of the blast pile is proposed. It uses the GA-LSSVM model to predict the shape parameters α and β of the Weibull function and sets multiple prediction points to predict the three-dimensional blasting pile morphology. By converting and fusing the parameters of the Kuz-Ram fragment prediction model, a distance prediction model of blast pile stratification is established and applied to the Weibull-GA-LSSVM model to achieve an automatic stratification of the blast pile. Through field application, the stratification design is continuously optimized for the best stratification position to realize the adaptive stratification. The results show that:(1)the Weibull-GA-LSSVM model can accurately predict the morphology of the blast pile with a good stability that the average relative error of the prediction results of the maximum forward distance of the blast pile is only 5.6% and the relative error of the prediction results of the looseness coefficient is mostly around 9%.(2)The Kuz-Ram-based blast pile stratification model can reasonably output the layer distance and number before blast, which ensures the shoveling efficiency after blast.(3) The optimal layer distance formula is derived to achieve the adaptive stratification of the blast pile, and the measurement accuracy of the fragment size distribution of the blast pile is significantly improved, which is closer to the overall fragment size distribution.

To study the response of mode Ⅰ cracks under impact loading, the dynamic fracture test on the single cleavage triangle (SCT) granite specimens with the lateral opening was carried out using a split Hopkinson pressure bar test system. The Hough transform method was used to quantitatively describe the distributions of the surface crack lengths and angles, and the relationship between them and the absorbed energy of the specimen was analyzed. The three-dimensional (3D) point cloud data of the fracture surface was obtained by using a 3D surface topography detection device, and a fracture surface reconstruction method based on the threshold detection of the fitting surface was proposed, which effectively solved the error problem caused by the appearance of error points in the 3D point cloud data of the fracture surface. The relationship between fracture surface roughness and absorbed energy was also discussed. The results show that the exponential distribution of crack length λ tends to increase, and the distribution of crack angles is more even with the increase in absorbed energy. There are relatively few cracks in the horizontal direction, and the cracks have obvious directionality when the dissipated energy of the specimen is lower, while the bending degree of the cracks is higher and the connectivity is better when the dissipated energy is higher. The fracture surface reconstruction method can complete the fracture surface processing better at 0.03-0.08 of the points in the x and y directions and the threshold of 0.25. The roughness statistical parameters of fracture surfaces A and B showed a decreasing trend with the increase in dissipated energy.